The role of entrepreneurship orientation in forming students' entrepreneurial intention through entrepreneurial education

Entrepreneurship is a global phenomenon because it contributes to economic growth, maintenance of social stability, and reduced unemployment. However, the role of entrepreneurial orientation in Vietnamese universities remains blurred. This study aims to understand the role of university education in shaping the entrepreneurial intention of Vietnamese students through entrepreneurial orientation, perceived desirability, and perceived feasibility. The PLS-SEM technique with SmartPLS 4 software tested the research model and hypotheses. The data set was collected from May 2023 to June 2023 via Google Forms with 411 respondents. The results show that entrepreneurial education has the most decisive impact on perceived desirability, followed by perceived feasibility, and both of these factors have a substantial impact on entrepreneurial orientation and entrepreneurial intention. Based on the results, the research has suggested practical implications that enhance entrepreneurial intention and promote the development of Vietnam's economy

Prognosis of neonatal tetanus in the modern management era: an observational study in 107 Vietnamese infants.

OBJECTIVES: Most data regarding the prognosis in neonatal tetanus originate from regions where limited resources have historically impeded management. It is not known whether recent improvements in critical care facilities in many low- and middle-income countries have affected indicators of a poor prognosis in neonatal tetanus. We aimed to determine the factors associated with worse outcomes in a Vietnamese hospital with neonatal intensive care facilities. METHODS: Data were collected from 107 cases of neonatal tetanus. Clinical features on admission were analyzed against mortality and a combined endpoint of 'death or prolonged hospital stay'. RESULTS: Multivariable analysis showed that only younger age (odds ratio (OR) for mortality 0.69, 95% confidence interval (CI) 0.48-0.98) and lower weight (OR for mortality 0.06, 95% CI 0.01-0.54) were significantly associated with both the combined endpoint and death. A shorter period of onset (OR 0.94, 95% CI 0.88-0.99), raised white cell count (OR 1.17, 95% CI 1.02-1.35), and time between first symptom and admission (OR 3.77, 95% CI 1.14-12.51) were also indicators of mortality. CONCLUSIONS: Risk factors for a poor outcome in neonatal tetanus in a setting with critical care facilities include younger age, lower weight, delay in admission, and leukocytosis

Co-pyrolysis of Chlorella vulgaris with plastic wastes: Thermal degradation, kinetics and Progressive Depth Swarm-Evolution (PDSE) neuro network-based optimization

The search of sustainable route for biofuel production from renewable biomass have garnered wide interest to seek for various routes without compromising the environment. Co-pyrolysis emerges as a promising thermochemical route that can improve the pyrolysis output from simultaneously processing more than two feedstocks in an inert atmosphere. This paper focuses on the kinetic modeling and neuro-evolution optimization in the application of catalytic co-pyrolysis of microalgae and plastic waste using HZSM-5 supported on limestone (HZSM-5/LS), in which co-pyrolysis of binary mixture of microalgae and plastic wastes (i.e. High-Density Polyethylene and Low-Density Polyethylene) was investigated over different heating rates. The results have shown a positive synergistic effect between the microalgae and polyethylene in which the apparent activation energies values have reduced significantly ( 20 kJ/mol) compared to that obtained by pyrolysis of individual microalgae component. The kinetic models reflect that the mixture of microalgae and Low-Density Polyethylene for use as co-pyrolysis feedstock requires activation energy that is 23% and 13% lower compared to that required by pure microalgae and the mixture of microalgae and High-Density Polyethylene, respectively. The Progressive Depth Swarm-Evolution (PDSE) was used for neural architecture search, which subsequently provided optimal reaction condition at 873 K can achieve 99.6 % of degradation rate using a tri-combination of LDPE (0.13 %) + HDPE (0.77 %) + MA (0.11 %) in the presence of HZSM-5/LS catalyst

High prevalence of plasmid-mediated quinolone resistance determinants in commensal members of the Enterobacteriaceae in Ho Chi Minh City, Vietnam

Antimicrobial-resistant pathogenic members of the Enterobacteriaceae are a well-defined global problem. We hypothesized that one of the main reservoirs of dissemination of antimicrobial resistance genes in Vietnam is non-pathogenic intestinal flora, and sought to isolate antimicrobial-resistant organisms from hospitalized patients and non-hospitalized healthy individuals in Ho Chi Minh City. The results identified substantial faecal carriage of gentamicin-, ceftazidime- and nalidixic acid-resistant members of the Enterobacteriaceae in both hospitalized patients and non-hospitalized healthy individuals. A high prevalence of quinolone resistance determinants was identified, particularly the qnrS gene, in both community- and hospital-associated strains. Furthermore, the results demonstrated that a combination of quinolone resistance determinants can confer resistance to nalidixic acid and ciprofloxacin, even in the apparent absence of additional chromosomal resistance mutations in wild-type strains and laboratory strains with transferred plasmids. These data suggest that intestinal commensal organisms are a significant reservoir for the dissemination of plasmid-mediated quinolone resistance in Ho Chi Minh City

Mitigating machine learning bias between high income and low–middle income countries for enhanced model fairness and generalizability

Collaborative efforts in artificial intelligence (AI) are increasingly common between high-income countries (HICs) and low- to middle-income countries (LMICs). Given the resource limitations often encountered by LMICs, collaboration becomes crucial for pooling resources, expertise, and knowledge. Despite the apparent advantages, ensuring the fairness and equity of these collaborative models is essential, especially considering the distinct differences between LMIC and HIC hospitals. In this study, we show that collaborative AI approaches can lead to divergent performance outcomes across HIC and LMIC settings, particularly in the presence of data imbalances. Through a real-world COVID-19 screening case study, we demonstrate that implementing algorithmic-level bias mitigation methods significantly improves outcome fairness between HIC and LMIC sites while maintaining high diagnostic sensitivity. We compare our results against previous benchmarks, utilizing datasets from four independent United Kingdom Hospitals and one Vietnamese hospital, representing HIC and LMIC settings, respectively

Acute Kidney Injury After Percutaneous Coronary Intervention Guided by Intravascular Ultrasound

Purpose We investigated the impact of intravascular ultrasound guidance on reducing the incidence of contrast-induced acute kidney injury (CI-AKI) in patients undergoing percutaneous coronary intervention (PCI). Methods Ninety-nine patients were enrolled in this prospective cohort who were not randomly assigned to angiography-guided percutaneous coronary intervention or intravascular ultrasound-guided percutaneous coronary intervention. The patients were hospitalized at the Vietnam National Heart Institute - Bach Mai Hospital between 2019 and 2020. Acute kidney injury incidence during hospitalization was the primary endpoint. Results A total of 99 patients were divided into two groups: the intravascular ultrasound-guided group (33 participants) and the angiography-guided group (66 participants). The mean ± SD contrast volume of each group was 95.2 ± 37.1 mL and 133.0 ± 36.0 mL for the ultrasound-guided and angiography-guided groups, with P \u3c 0.0001. Intravascular imaging-guided percutaneous coronary intervention (IVUS-guided PCI) was associated with reduced acute kidney injury incidence during hospitalization: 0.0% vs. 12.12% and P = 0.049. Conclusions Intravascular ultrasound is a safe imaging tool that guides percutaneous coronary intervention and significantly reduces the rate of acute kidney injury compared to angiography alone. Patients who have a high chance of experiencing acute kidney injury benefit from using intravascular ultrasound

Generalizability assessment of AI models across hospitals in a low-middle and high income country

The integration of artificial intelligence (AI) into healthcare systems within low-middle income countries (LMICs) has emerged as a central focus for various initiatives aiming to improve healthcare access and delivery quality. In contrast to high-income countries (HICs), which often possess the resources and infrastructure to adopt innovative healthcare technologies, LMICs confront resource limitations such as insufficient funding, outdated infrastructure, limited digital data, and a shortage of technical expertise. Consequently, many algorithms initially trained on data from non-LMIC settings are now being employed in LMIC contexts. However, the effectiveness of these systems in LMICs can be compromised when the unique local contexts and requirements are not adequately considered. In this study, we evaluate the feasibility of utilizing models developed in the United Kingdom (a HIC) within hospitals in Vietnam (a LMIC). Consequently, we present and discuss practical methodologies aimed at improving model performance, emphasizing the critical importance of tailoring solutions to the distinct healthcare systems found in LMICs. Our findings emphasize the necessity for collaborative initiatives and solutions that are sensitive to the local context in order to effectively tackle the healthcare challenges that are unique to these regions

Heart rate variability measured from wearable devices as a marker of disease severity in tetanus

Tetanus is a disease associated with significant morbidity and mortality. Heart rate variability (HRV) is an objective clinical marker with potential value in tetanus. This study aimed to investigate the use of wearable devices to collect HRV data and the relationship between HRV and tetanus severity. Data were collected from 110 patients admitted to the intensive care unit in a tertiary hospital in Vietnam. HRV indices were calculated from 5-minute segments of 24-hour electrocardiogram recordings collected using wearable devices. HRV was found to be inversely related to disease severity. The standard deviation of NN intervals and interquartile range of RR intervals (IRRR) were significantly associated with the presence of muscle spasms; low frequency (LF) and high frequency (HF) indices were significantly associated with severe respiratory compromise; and the standard deviation of differences between adjacent NN intervals, root mean square of successive differences between normal heartbeats, LF to HF ratio, total frequency power, and IRRR, were significantly associated with autonomic nervous system dysfunction. The findings support the potential value of HRV as a marker for tetanus severity, identifying specific indices associated with clinical severity thresholds. Data were recorded using wearable devices, demonstrating this approach in resource-limited settings where most tetanus occurs

Transport Jc in Bulk Superconductors: A Practical Approach?

The characterisation of the critical current density of bulk high temperature superconductors is typically performed using magnetometry, which involves numerous assumptions including, significantly, that Jc within the sample is uniform. Unfortunately, magnetometry is particularly challenging to apply where a local measurement of Jc across a feature, such as a grain boundary, is desired. Although transport measurements appear to be an attractive alternative to magnetization, it is extremely challenging to reduce the cross-sectional area of a bulk sample sufficiently to achieve a sufficiently low critical current that can be generated by a practical current source. In the work described here, we present a technique that enables transport measurements to be performed on sections of bulk superconductors. Metallographic techniques and resin reinforcement were used to create an I-shaped sample of bulk superconductor from a section of Gd-Ba-Cu-O containing 15 wt % Ag2O. The resulting superconducting track had a cross-sectional area of 0.44 mm2. The sample was found to support a critical current of 110 A using a field criterion in the narrowed track region of 1 μV cm-1. We conclude, therefore, that it is possible to measure critical current densities in excess of 2.5 x 108 A m-2 in sections of a bulk superconductor.This work was supported by the Engineering and Physical Sciences Research Council, via a Doctoral Training Award (grant number is EP/L504920/1) and funding from grant number EP/K02910X/1. This work was also supported by the Boeing Company. All data are provided in full in the results section of this paper.This is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/10.1109/TASC.2016.253764

Clinical evaluation of AI-assisted muscle ultrasound for monitoring muscle wasting in ICU patients

Muscle ultrasound has been shown to be a valid and safe imaging modality to assess muscle wasting in critically ill patients in the intensive care unit (ICU). This typically involves manual delineation to measure the rectus femoris cross-sectional area (RFCSA), which is a subjective, time-consuming, and laborious task that requires significant expertise. We aimed to develop and evaluate an AI tool that performs automated recognition and measurement of RFCSA to support non-expert operators in measurement of the RFCSA using muscle ultrasound. Twenty patients were recruited between Feb 2023 and July 2023 and were randomized sequentially to operators using AI (n = 10) or non-AI (n = 10). Muscle loss during ICU stay was similar for both methods: 26 ± 15% for AI and 23 ± 11% for the non-AI, respectively (p = 0.13). In total 59 ultrasound examinations were carried out (30 without AI and 29 with AI). When assisted by our AI tool, the operators showed less variability between measurements with higher intraclass correlation coefficients (ICCs 0.999 95% CI 0.998–0.999 vs. 0.982 95% CI 0.962–0.993) and lower Bland Altman limits of agreement (± 1.9% vs. ± 6.6%) compared to not using the AI tool. The time spent on scans reduced significantly from a median of 19.6 min (IQR 16.9–21.7) to 9.4 min (IQR 7.2–11.7) compared to when using the AI tool (p < 0.001). AI-assisted muscle ultrasound removes the need for manual tracing, increases reproducibility and saves time. This system may aid monitoring muscle size in ICU patients assisting rehabilitation programmes